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Course Description

This course provides an overview of the analysis methods of genetic and genomic data, as well as integration of diverse ‘omics data. Topics include an introduction to high-throughput technologies for the generation of genetics and genomic data, including DNA variants and gene expression data that can be measured though next generation sequencing technologies, proteomics and metabolomic data, and the microbiome. Main stream methods of analysis for each data type, as well as their integration, will be described. A final project with will involve analysis of a publicly available dataset.

Students should be trained in the medical sciences (e.g., MD, DO, DDS, DVM, PharmD), have advanced biomedical or clinical degrees, be enrolled in an advanced biomedical or clinical degree program, or have substantial biomedical or clinical research experience. 

Basic Enrollment Requirements: Unofficial Transcript – Bachelor’s. You will be contacted after registration for required evidence of immunization.

Instructor Approval: Required. Please email the instructor of this course to request permission to enroll. We typically recommend including a resume, your educational history, and 2-3 sentences as to why you are interested in taking the course. You may register for this course before receiving approval, but your enrollment will not be confirmed until approval is received. Please contact us at Courses@tufts.edu if you have not heard back from your instructor.

Refund Policy: The refund policy for Courses at Tufts offerings is dependent on the offering type: whether the offering is a course, workshop or short course, or in-demand offering. Please refer to the section details to confirm the type of offering as well as any exceptions to the standard refund policy. The refund policies for each offering type and instruction mode are viewable here: https://universitycollege.tufts.edu/policies/refunds#Courses-at-Tufts-(Academic-Year--Summer-Session)

Remission Eligible: Yes; first day of term; all university policies apply.

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